Chris N. Potts

TL;DR: In this article, a branch-and-bound algorithm is presented for the permutation flow-shop problem, in which the objective is to minimize the maximum completion time, and a branching procedure is used in which jobs both at the beginning and at the end of the schedule have been fixed.

TL;DR: General precedence constrained dynamic programming algorithms and special-purpose decomposition algorithms are presented and results for problems with up to 100 jobs are given.

TL;DR: This work considers various single machine scheduling problems in which the processing time of a job depends either on its position in a processing sequence or on its start time, and shows that the objective function is priority-generating and therefore the corresponding scheduling problem under series-parallel precedence constraints is polynomially solvable.

TL;DR: This paper develops algorithms to minimize the makespan for a single job in three-stage production processes and proposes an algorithm which computes the minimum makespan in O(log s) time.

TL;DR: In this article, an Iterated Local Search (ILS) heuristic was proposed to solve the single machine total weighted tardiness problem with sequence-dependent setup times (often known as problem ) where a given set of jobs to be sequenced on a single machine, where a setup time is required before each job that depends on both the preceding job and the job to be processed next.